Overview

Dataset statistics

Number of variables10
Number of observations100000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.6 MiB
Average record size in memory80.0 B

Variable types

Numeric10

Warnings

m1 has unique values Unique
m2 has unique values Unique
G has unique values Unique
x1 has unique values Unique
x2 has unique values Unique
y1 has unique values Unique
y2 has unique values Unique
z1 has unique values Unique
z2 has unique values Unique
target has unique values Unique

Reproduction

Analysis started2021-07-29 16:23:11.693472
Analysis finished2021-07-29 16:38:22.644129
Duration15 minutes and 10.95 seconds
Software versionpandas-profiling v3.0.0
Download configurationconfig.json

Variables

m1
Real number (ℝ≥0)

UNIQUE

Distinct100000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.499521481
Minimum1.000005128
Maximum1.999983278
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2021-07-29T16:38:22.713836image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum1.000005128
5-th percentile1.050618714
Q11.25114422
median1.498828347
Q31.747573271
95-th percentile1.949641741
Maximum1.999983278
Range0.9999781499
Interquartile range (IQR)0.4964290519

Descriptive statistics

Standard deviation0.2879472974
Coefficient of variation (CV)0.1920261237
Kurtosis-1.192341485
Mean1.499521481
Median Absolute Deviation (MAD)0.2482611242
Skewness0.004513730183
Sum149952.1481
Variance0.08291364608
MonotonicityNot monotonic
2021-07-29T16:38:22.859248image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.8594438261
 
< 0.1%
1.001396831
 
< 0.1%
1.5468815741
 
< 0.1%
1.0626485491
 
< 0.1%
1.2527513331
 
< 0.1%
1.3066320171
 
< 0.1%
1.3986227971
 
< 0.1%
1.1543867231
 
< 0.1%
1.1425880261
 
< 0.1%
1.1778852511
 
< 0.1%
Other values (99990)99990
> 99.9%
ValueCountFrequency (%)
1.0000051281
< 0.1%
1.0000123111
< 0.1%
1.0000206961
< 0.1%
1.0000246541
< 0.1%
1.0000321251
< 0.1%
1.0000408351
< 0.1%
1.0000550731
< 0.1%
1.0000708841
< 0.1%
1.0000821761
< 0.1%
1.0000882321
< 0.1%
ValueCountFrequency (%)
1.9999832781
< 0.1%
1.9999780941
< 0.1%
1.9999779921
< 0.1%
1.999968891
< 0.1%
1.9999685031
< 0.1%
1.999965631
< 0.1%
1.9999499411
< 0.1%
1.9999465781
< 0.1%
1.999944311
< 0.1%
1.9999116721
< 0.1%

m2
Real number (ℝ≥0)

UNIQUE

Distinct100000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.498730947
Minimum1.000008385
Maximum1.999977481
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2021-07-29T16:38:23.004048image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum1.000008385
5-th percentile1.049713533
Q11.248477014
median1.4968789
Q31.749218027
95-th percentile1.950490596
Maximum1.999977481
Range0.9999690963
Interquartile range (IQR)0.5007410129

Descriptive statistics

Standard deviation0.2890472884
Coefficient of variation (CV)0.1928613598
Kurtosis-1.202847442
Mean1.498730947
Median Absolute Deviation (MAD)0.2503288852
Skewness0.01245247772
Sum149873.0947
Variance0.08354833491
MonotonicityNot monotonic
2021-07-29T16:38:23.146603image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.5896491311
 
< 0.1%
1.6920214131
 
< 0.1%
1.7399910391
 
< 0.1%
1.967995871
 
< 0.1%
1.2053424711
 
< 0.1%
1.5785662411
 
< 0.1%
1.7367152791
 
< 0.1%
1.5685503741
 
< 0.1%
1.8635213641
 
< 0.1%
1.2356420261
 
< 0.1%
Other values (99990)99990
> 99.9%
ValueCountFrequency (%)
1.0000083851
< 0.1%
1.0000375381
< 0.1%
1.0000684821
< 0.1%
1.0000888631
< 0.1%
1.0000975471
< 0.1%
1.0001089711
< 0.1%
1.0001107151
< 0.1%
1.000121281
< 0.1%
1.0001388861
< 0.1%
1.0001406161
< 0.1%
ValueCountFrequency (%)
1.9999774811
< 0.1%
1.999955891
< 0.1%
1.9999534021
< 0.1%
1.99991941
< 0.1%
1.999900761
< 0.1%
1.9998978221
< 0.1%
1.9998970561
< 0.1%
1.9998802721
< 0.1%
1.9998743311
< 0.1%
1.9998742161
< 0.1%

G
Real number (ℝ≥0)

UNIQUE

Distinct100000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.500207042
Minimum1.000015133
Maximum1.999997273
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2021-07-29T16:38:23.290052image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum1.000015133
5-th percentile1.049980448
Q11.250146826
median1.500064692
Q31.750464768
95-th percentile1.950184328
Maximum1.999997273
Range0.9999821403
Interquartile range (IQR)0.5003179424

Descriptive statistics

Standard deviation0.2887145335
Coefficient of variation (CV)0.1924497922
Kurtosis-1.200997295
Mean1.500207042
Median Absolute Deviation (MAD)0.2501248995
Skewness-0.00292001358
Sum150020.7042
Variance0.08335608187
MonotonicityNot monotonic
2021-07-29T16:38:23.433222image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.5975268941
 
< 0.1%
1.0716294731
 
< 0.1%
1.5230661121
 
< 0.1%
1.0371998061
 
< 0.1%
1.0174703141
 
< 0.1%
1.9222110421
 
< 0.1%
1.3955193561
 
< 0.1%
1.330438851
 
< 0.1%
1.7490223871
 
< 0.1%
1.939076781
 
< 0.1%
Other values (99990)99990
> 99.9%
ValueCountFrequency (%)
1.0000151331
< 0.1%
1.0000278571
< 0.1%
1.0000305051
< 0.1%
1.0000397851
< 0.1%
1.000049721
< 0.1%
1.0000672161
< 0.1%
1.0000759471
< 0.1%
1.0000771111
< 0.1%
1.0000801171
< 0.1%
1.0000820521
< 0.1%
ValueCountFrequency (%)
1.9999972731
< 0.1%
1.9999931051
< 0.1%
1.9999741161
< 0.1%
1.999965861
< 0.1%
1.9999637631
< 0.1%
1.999941091
< 0.1%
1.9999379161
< 0.1%
1.9999371671
< 0.1%
1.9999366731
< 0.1%
1.9999359311
< 0.1%

x1
Real number (ℝ≥0)

UNIQUE

Distinct100000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.49947053
Minimum3.000006005
Maximum3.99999401
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2021-07-29T16:38:23.577198image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum3.000006005
5-th percentile3.049983126
Q13.248893144
median3.498089591
Q33.749887996
95-th percentile3.950687271
Maximum3.99999401
Range0.9999880048
Interquartile range (IQR)0.5009948519

Descriptive statistics

Standard deviation0.2891707558
Coefficient of variation (CV)0.0826327164
Kurtosis-1.203669478
Mean3.49947053
Median Absolute Deviation (MAD)0.250611619
Skewness0.005299180642
Sum349947.053
Variance0.08361972603
MonotonicityNot monotonic
2021-07-29T16:38:23.720024image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.2986410851
 
< 0.1%
3.5858948511
 
< 0.1%
3.7765489151
 
< 0.1%
3.2330342341
 
< 0.1%
3.1172772081
 
< 0.1%
3.7201486281
 
< 0.1%
3.4736029691
 
< 0.1%
3.5759903731
 
< 0.1%
3.8630495011
 
< 0.1%
3.2637617111
 
< 0.1%
Other values (99990)99990
> 99.9%
ValueCountFrequency (%)
3.0000060051
< 0.1%
3.0000080261
< 0.1%
3.0000154771
< 0.1%
3.0000415521
< 0.1%
3.0000428771
< 0.1%
3.0000789851
< 0.1%
3.0000865071
< 0.1%
3.0000937321
< 0.1%
3.0001027861
< 0.1%
3.000110971
< 0.1%
ValueCountFrequency (%)
3.999994011
< 0.1%
3.9999828981
< 0.1%
3.9999807641
< 0.1%
3.9999534751
< 0.1%
3.9999445931
< 0.1%
3.9999405451
< 0.1%
3.9999310751
< 0.1%
3.9999270891
< 0.1%
3.9999119311
< 0.1%
3.9999055321
< 0.1%

x2
Real number (ℝ≥0)

UNIQUE

Distinct100000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.499411646
Minimum1.000005301
Maximum1.999985039
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2021-07-29T16:38:23.863612image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum1.000005301
5-th percentile1.050136311
Q11.248891739
median1.500171072
Q31.750174642
95-th percentile1.949761594
Maximum1.999985039
Range0.9999797385
Interquartile range (IQR)0.5012829029

Descriptive statistics

Standard deviation0.2887546378
Coefficient of variation (CV)0.1925786281
Kurtosis-1.201071705
Mean1.499411646
Median Absolute Deviation (MAD)0.2506987092
Skewness0.001131135315
Sum149941.1646
Variance0.08337924083
MonotonicityNot monotonic
2021-07-29T16:38:24.142765image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.5731432561
 
< 0.1%
1.3250734581
 
< 0.1%
1.0471667261
 
< 0.1%
1.1430650961
 
< 0.1%
1.6868095151
 
< 0.1%
1.6670747221
 
< 0.1%
1.5831678471
 
< 0.1%
1.898229151
 
< 0.1%
1.530852811
 
< 0.1%
1.6111000291
 
< 0.1%
Other values (99990)99990
> 99.9%
ValueCountFrequency (%)
1.0000053011
< 0.1%
1.0000092221
< 0.1%
1.0000119211
< 0.1%
1.0000131911
< 0.1%
1.0000261611
< 0.1%
1.000028481
< 0.1%
1.0000420231
< 0.1%
1.0000439071
< 0.1%
1.0000678021
< 0.1%
1.0000704381
< 0.1%
ValueCountFrequency (%)
1.9999850391
< 0.1%
1.9999843361
< 0.1%
1.9999827041
< 0.1%
1.9999771491
< 0.1%
1.9999707371
< 0.1%
1.9999560321
< 0.1%
1.9999557321
< 0.1%
1.9999387571
< 0.1%
1.9999305481
< 0.1%
1.9999254471
< 0.1%

y1
Real number (ℝ≥0)

UNIQUE

Distinct100000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.500973501
Minimum3.000007884
Maximum3.999991252
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2021-07-29T16:38:24.287769image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum3.000007884
5-th percentile3.050650843
Q13.25116847
median3.501583401
Q33.751156102
95-th percentile3.950891801
Maximum3.999991252
Range0.9999833682
Interquartile range (IQR)0.499987632

Descriptive statistics

Standard deviation0.2890080023
Coefficient of variation (CV)0.08255075402
Kurtosis-1.200833688
Mean3.500973501
Median Absolute Deviation (MAD)0.2500108177
Skewness-0.003180587228
Sum350097.3501
Variance0.08352562538
MonotonicityNot monotonic
2021-07-29T16:38:24.430610image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.5492691031
 
< 0.1%
3.7412941571
 
< 0.1%
3.0731453281
 
< 0.1%
3.7831372081
 
< 0.1%
3.7358690731
 
< 0.1%
3.7479517881
 
< 0.1%
3.2311592371
 
< 0.1%
3.4021076391
 
< 0.1%
3.6563221841
 
< 0.1%
3.0569264251
 
< 0.1%
Other values (99990)99990
> 99.9%
ValueCountFrequency (%)
3.0000078841
< 0.1%
3.0000083611
< 0.1%
3.0000342371
< 0.1%
3.0000419091
< 0.1%
3.0000711931
< 0.1%
3.0000842241
< 0.1%
3.0000885391
< 0.1%
3.0000952151
< 0.1%
3.0000981031
< 0.1%
3.0001000091
< 0.1%
ValueCountFrequency (%)
3.9999912521
< 0.1%
3.9999438131
< 0.1%
3.9999049411
< 0.1%
3.9998850951
< 0.1%
3.9998786041
< 0.1%
3.9998576261
< 0.1%
3.9998569531
< 0.1%
3.9998525141
< 0.1%
3.9998525071
< 0.1%
3.9998489311
< 0.1%

y2
Real number (ℝ≥0)

UNIQUE

Distinct100000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.49946812
Minimum1.000009943
Maximum1.999995449
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2021-07-29T16:38:24.574533image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum1.000009943
5-th percentile1.049964578
Q11.248836334
median1.49852004
Q31.750667666
95-th percentile1.949307986
Maximum1.999995449
Range0.9999855056
Interquartile range (IQR)0.5018313326

Descriptive statistics

Standard deviation0.2887901719
Coefficient of variation (CV)0.1925950729
Kurtosis-1.201995403
Mean1.49946812
Median Absolute Deviation (MAD)0.2510129411
Skewness0.003516958565
Sum149946.812
Variance0.08339976339
MonotonicityNot monotonic
2021-07-29T16:38:24.717350image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.2200626811
 
< 0.1%
1.6518043491
 
< 0.1%
1.4800282341
 
< 0.1%
1.8294646211
 
< 0.1%
1.6604456081
 
< 0.1%
1.1297710051
 
< 0.1%
1.1420148081
 
< 0.1%
1.7514127341
 
< 0.1%
1.7822014681
 
< 0.1%
1.6330599291
 
< 0.1%
Other values (99990)99990
> 99.9%
ValueCountFrequency (%)
1.0000099431
< 0.1%
1.00003581
< 0.1%
1.0000703091
< 0.1%
1.0000821361
< 0.1%
1.0001322881
< 0.1%
1.0001419091
< 0.1%
1.0001432641
< 0.1%
1.0001452211
< 0.1%
1.0001489071
< 0.1%
1.0001516631
< 0.1%
ValueCountFrequency (%)
1.9999954491
< 0.1%
1.9999845771
< 0.1%
1.9999839721
< 0.1%
1.9999574951
< 0.1%
1.9999520471
< 0.1%
1.9999474471
< 0.1%
1.9999376821
< 0.1%
1.9999376691
< 0.1%
1.9999341131
< 0.1%
1.9999314961
< 0.1%

z1
Real number (ℝ≥0)

UNIQUE

Distinct100000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.49965374
Minimum3.00001609
Maximum3.999984578
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2021-07-29T16:38:24.861572image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum3.00001609
5-th percentile3.049623124
Q13.249744371
median3.500034009
Q33.749513234
95-th percentile3.951250738
Maximum3.999984578
Range0.9999684881
Interquartile range (IQR)0.4997688635

Descriptive statistics

Standard deviation0.2889522965
Coefficient of variation (CV)0.08256596738
Kurtosis-1.198844002
Mean3.49965374
Median Absolute Deviation (MAD)0.2498376753
Skewness0.00439655632
Sum349965.374
Variance0.08349342967
MonotonicityNot monotonic
2021-07-29T16:38:24.998729image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.6874490341
 
< 0.1%
3.1108652051
 
< 0.1%
3.3141124441
 
< 0.1%
3.3327498521
 
< 0.1%
3.737004941
 
< 0.1%
3.0972040911
 
< 0.1%
3.0581360061
 
< 0.1%
3.0484973821
 
< 0.1%
3.1653855681
 
< 0.1%
3.7666495551
 
< 0.1%
Other values (99990)99990
> 99.9%
ValueCountFrequency (%)
3.000016091
< 0.1%
3.0000264231
< 0.1%
3.0000309541
< 0.1%
3.0000413551
< 0.1%
3.000050971
< 0.1%
3.0000519811
< 0.1%
3.0000549861
< 0.1%
3.0000570421
< 0.1%
3.0000588631
< 0.1%
3.0000607191
< 0.1%
ValueCountFrequency (%)
3.9999845781
< 0.1%
3.9999612841
< 0.1%
3.9999582061
< 0.1%
3.9999556441
< 0.1%
3.9999531281
< 0.1%
3.9999479531
< 0.1%
3.9999267111
< 0.1%
3.9999075251
< 0.1%
3.9998986771
< 0.1%
3.9998863951
< 0.1%

z2
Real number (ℝ≥0)

UNIQUE

Distinct100000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.501224331
Minimum1.00001223
Maximum1.999989857
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2021-07-29T16:38:25.137643image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum1.00001223
5-th percentile1.050695473
Q11.250447426
median1.502058621
Q31.752104598
95-th percentile1.950350897
Maximum1.999989857
Range0.9999776267
Interquartile range (IQR)0.5016571717

Descriptive statistics

Standard deviation0.2889398688
Coefficient of variation (CV)0.1924694816
Kurtosis-1.20310883
Mean1.501224331
Median Absolute Deviation (MAD)0.2508835962
Skewness-0.004460869805
Sum150122.4331
Variance0.08348624777
MonotonicityNot monotonic
2021-07-29T16:38:25.274609image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0966342331
 
< 0.1%
1.2744291081
 
< 0.1%
1.5772089541
 
< 0.1%
1.0619736521
 
< 0.1%
1.2754027041
 
< 0.1%
1.5841135541
 
< 0.1%
1.7359917851
 
< 0.1%
1.200444741
 
< 0.1%
1.1573047641
 
< 0.1%
1.6249509941
 
< 0.1%
Other values (99990)99990
> 99.9%
ValueCountFrequency (%)
1.000012231
< 0.1%
1.0000177221
< 0.1%
1.0000221061
< 0.1%
1.0000484341
< 0.1%
1.0000622131
< 0.1%
1.0000631991
< 0.1%
1.0000940271
< 0.1%
1.0001032671
< 0.1%
1.0001088581
< 0.1%
1.0001113531
< 0.1%
ValueCountFrequency (%)
1.9999898571
< 0.1%
1.9999579181
< 0.1%
1.9999559391
< 0.1%
1.9999484671
< 0.1%
1.9999433861
< 0.1%
1.9999277871
< 0.1%
1.9999255251
< 0.1%
1.9999236661
< 0.1%
1.9999160081
< 0.1%
1.9999137521
< 0.1%

target
Real number (ℝ≥0)

UNIQUE

Distinct100000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2852173208
Minimum0.05562133742
Maximum1.266845902
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2021-07-29T16:38:25.408682image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Quantile statistics

Minimum0.05562133742
5-th percentile0.1311316623
Q10.196685105
median0.2622717308
Q30.3478018986
95-th percentile0.5175310634
Maximum1.266845902
Range1.211224565
Interquartile range (IQR)0.1511167936

Descriptive statistics

Standard deviation0.1229473334
Coefficient of variation (CV)0.4310654523
Kurtosis2.669974328
Mean0.2852173208
Median Absolute Deviation (MAD)0.07304549469
Skewness1.258498525
Sum28521.73208
Variance0.01511604679
MonotonicityNot monotonic
2021-07-29T16:38:25.547728image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.31241235311
 
< 0.1%
0.14130615281
 
< 0.1%
0.31523402241
 
< 0.1%
0.16258494281
 
< 0.1%
0.12377034961
 
< 0.1%
0.29677640781
 
< 0.1%
0.34994969491
 
< 0.1%
0.26901737851
 
< 0.1%
0.28682410231
 
< 0.1%
0.30198499881
 
< 0.1%
Other values (99990)99990
> 99.9%
ValueCountFrequency (%)
0.055621337421
< 0.1%
0.058005079381
< 0.1%
0.058892660111
< 0.1%
0.060905481191
< 0.1%
0.061909223961
< 0.1%
0.0621177761
< 0.1%
0.06376307381
< 0.1%
0.064004837681
< 0.1%
0.064381506291
< 0.1%
0.065170270641
< 0.1%
ValueCountFrequency (%)
1.2668459021
< 0.1%
1.2188180191
< 0.1%
1.2150819641
< 0.1%
1.202782911
< 0.1%
1.1932482651
< 0.1%
1.1886196631
< 0.1%
1.175454081
< 0.1%
1.1726736121
< 0.1%
1.1690923031
< 0.1%
1.1604271851
< 0.1%

Interactions

2021-07-29T16:38:08.652336image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:08.781745image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:08.908323image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:09.035784image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:09.162258image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:09.288143image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:09.416397image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:09.543123image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:09.670114image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:09.797722image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:09.927227image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:10.197445image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:10.323534image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:10.449017image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:10.577051image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:10.703688image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:10.831154image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:10.959629image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:11.085309image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:11.211186image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:11.340403image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:11.463836image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:11.587481image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:11.714596image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:11.843697image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:11.972308image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:12.100986image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:12.228691image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:12.354218image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:12.480681image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:12.609895image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:12.737142image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:12.863770image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:13.126013image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:13.251301image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:13.376211image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:13.499741image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:13.624177image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:13.747676image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:13.873145image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:14.002928image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:14.129018image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:14.253818image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:14.378166image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:14.501683image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:14.627850image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:14.753560image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:14.881509image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:15.011689image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:15.141351image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:15.272741image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:15.399729image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:15.528628image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:15.655509image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:15.782055image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:16.044268image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:16.171064image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:16.296015image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:16.421998image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:16.548108image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:16.677257image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:16.804507image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:16.931352image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:17.056566image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:17.184099image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:17.309567image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:17.435248image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:17.560875image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:17.688286image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:17.814476image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:17.944702image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:18.070607image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:18.197492image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:18.324227image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:18.450396image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:18.577235image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:18.703457image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:18.970324image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:19.096879image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:19.224116image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:19.354132image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:19.480449image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:19.606359image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:19.732428image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:19.857988image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:19.982934image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:20.109844image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:20.237149image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:20.362772image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:20.488559image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:20.618761image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:20.749346image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:20.879932image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:21.011393image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:21.141928image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:21.271909image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:21.400934image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:21.531123image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:21.798715image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
2021-07-29T16:38:21.934906image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Correlations

2021-07-29T16:38:25.670853image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-07-29T16:38:25.971095image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-07-29T16:38:26.138251image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-07-29T16:38:26.304715image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2021-07-29T16:38:22.145559image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
A simple visualization of nullity by column.
2021-07-29T16:38:22.377654image/svg+xmlMatplotlib v3.4.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

m1m2Gx1x2y1y2z1z2target
01.8594441.5896491.5975273.2986411.5731433.5492691.2200633.6874491.0966340.312412
11.0318071.1906071.2896903.7219031.2879283.5768421.6146923.6879841.0495260.094669
21.9947731.8367841.0556123.4465541.6118363.3412931.3992403.4685441.2848000.324842
31.2549281.5255631.9986973.1362231.1498453.9157131.9841263.5087541.7388050.353991
41.9542771.0813311.6524773.0353661.6133193.8895431.7312483.3038511.3650710.334509
51.2841191.2204121.5910303.4598821.6975233.0030421.8481283.7575161.2163950.228814
61.8543731.9552081.4769763.9619651.4067583.2117651.4525463.4825261.9724740.449846
71.2747991.6764551.6722993.4592641.7082023.0632151.8966843.8516361.9122170.436467
81.9625871.2669631.5444823.6805861.1821933.2017141.0268843.0022081.0882250.262408
91.5817141.8111611.1221203.3082751.5710973.5542231.8773313.3546461.1169250.296626

Last rows

m1m2Gx1x2y1y2z1z2target
999901.7898301.3037901.7837363.4371201.7764033.5991561.2304783.2566371.8577970.403130
999911.1704741.5889781.8841983.3381481.2278533.7837541.1091323.5361741.8193280.240774
999921.9991791.1776731.1491513.9605021.9367353.1080471.1772113.7668681.5932090.215605
999931.0186651.5426281.4205563.1629361.5466483.6557821.5335983.4419191.2955030.190417
999941.5353881.1005891.0786273.3584681.8932643.6329841.2771383.6633471.7281580.159302
999951.2578591.9252011.9137813.4827321.5249703.5794031.7957913.2645311.9946270.537221
999961.0604141.0027411.2720413.2442591.2812413.3297931.1768423.9484981.6606310.098564
999971.2743331.8329531.1481153.1205241.8981373.2971921.1055283.9414581.4684380.216037
999981.7866281.8026001.5759993.6975791.0565553.6139651.2126193.1335371.1220680.302346
999991.8179861.7073591.3653373.9177961.4981023.7152801.9560603.3232441.7384380.369759